Role & responsibilities The AI Engineer will design, build, deploy, and operate production-grade Large Language Model (LLM) solutions. This role focuses on engineering rigorturning LLM capabilities into reliable, scalable, and secure enterprise applications, and continuously improving them based on performance, cost, and user feedback.

Key Responsibilities
Design and build LLM-powered applications using proprietary and open-source models.
Implement prompt engineering, Retrieval-Augmented Generation (RAG), tool/function calling, and agent workflows.
Deploy LLM solutions into cloud and enterprise settings with scalability and reliability.
Build inference APIs, microservices, and CI/CD pipelines for AI applications.
Monitor model quality, latency, cost, drift, and hallucinations in production.
Fine-tune and enhance models using parameter-productive techniques where required.
Optimize inference performance using caching, batching, quantization,



and prompt optimization.
Ensure security, privacy, and responsible AI guardrails in all deployments.
Collaborate with product, platform, and engineering teams to deliver enterprise AI solutions.

Preferred candidate profile
Solid programming skills in Python;

experience with backend APIs.
Hands-on experience with LLM frameworks (LangChain, LlamaIndex, or equivalent).
Experience building RAG pipelines using vector databases.
Knowledge of Docker, Kubernetes, cloud platforms, and CI/CD pipelines.
Familiarity with LLMOps / MLOps tools and monitoring systems.

Experience Level
10 to 18 years of overall software or ML engineering experience.
8+ years of hands-on experience delivering LLM or Generative AI solutions in production.

📌 Genai Lead/architect Hyderabad (India)
🏢 HCLTech
📍 India